Data exploration combining visual inspection and analytic search

ABSTRACT

A computer device displays a graph of a data set. The computer device includes a hybrid data analysis and visualization tool to query implicit properties of data items in the data set that are not evident upon visual inspection of the graph of the data set itself. The hybrid data analysis and visualization tool combines the graph of the data set with analog representations of data query results for visual data exploration.

BACKGROUND

A plot is a graphical technique for representing a data set, usually asa graph showing the relationship between two or more variables. Incommon two-dimensional plots or graphs, data items are plottedsimultaneously, for example, with respect to two variables along twoperpendicular axes (e.g., X and Y axis). The graphs provide a visualrepresentation of the relationship between variables. A value for eachdata item displayed can be identified with respect to each of the twofeatured variables by using the axes labels.

Plots or graphs are used to present data visually in mathematics,sciences, engineering, technology, finance, business and other fields. Agoal of data visualization is to communicate information clearly andeffectively through graphical means. Statistics and data analysisprocedures generally yield their output in numeric or tabular form.Graphical techniques allow such results to be displayed in pictorialform as plots including, for example, scatter plots, histograms,probability plots, spaghetti plots, residual plots, box plots, blockplots and biplots, etc. Plots or graphs can be useful for humans who canquickly comprehend and derive an understanding of data from a visualinspection of a picture that does not come as easily from perusing listsor tables of numeric values.

Computer systems and software for presenting data visually in the formof the various types of plots are widely available. Although thegraphical data plots can convey information by presenting a data setvisually, interpretation of the information (i.e., the plotted data)depends on the mental activities of the viewer. In general, the viewer'sactivities are limited to visual inspection, which cannot be tracked byobserving viewer or screen behavior. Exploration of a data set displayedin a graph, beyond mere visual inspection, requires further analysis ofthe data set (and related data) using, for example, statistical packagesor analytics software (e.g., business analytics software).

Consideration is being given to systems and methods which combine visualinspection and analytic search functions for exploration of data sets.

SUMMARY

In a general aspect, a computer device for data exploration of includesa processor and a hybrid data analysis and visualization tool (“datavisualization tool” for short). The data visualization tool isconfigured to integrate analog representations of data query resultsinto a graph of a data set. An analog representation may be a value orvariable in analog or continuous form. The data query results may relateto implicit properties and relationships of data items in the data set.The implicit properties may in particular be properties that are notevident upon visual inspection of the graph of the data set itself. Thedata visualization tool may provide a user with interactive features forformulating and submitting data queries relative to a target data itemin the graph, and for viewing analog representations of the data queryresults visually in combination with the graph of the data set on a userinterface.

In another aspect, the user interface provided by the data analysis toolincludes a visual data display panel and a query entry panel. The queryentry panel includes one or more input elements for entering queryparameters (e.g., for pre-defined query components). The pre-definedquery components may, for example, include a question on a degree ofsimilarity between the data items and the target data item with respectto an implicit property of the data items, and/or a question on anorientation of the data items toward the target data item. Thepre-defined query components may also include a time criterion. The oneor more input elements for entering query parameters for pre-definedquery components include one or more of check boxes, menus, analogslider scales, buttons, label buttons, radio buttons, sliders, droplists, and text boxes displayed on the query entry panel.

In another aspect, the one or more input elements for entering queryparameters on the query entry panel may be displayed with pictorial oranalog value representations of the query parameters. The data analysistool may be configured use the pictorial or analog value representationsof the query parameters on the query entry panel as the analogrepresentations of data query results to enhance the graph of the dataset.

In a general aspect, a computer-implemented method for exploring datathat is displayed in a data plot includes providing a computer-userinterface configured for a user to formulate and submit a query on thedata that is displayed in the data plot, and displaying the data plot onthe computer-user interface in combination with analog representationsof the results of the query. The computer-user interface may presentinput elements for entering query parameters for one or more pre-definedquery components. The input elements may, for example, include inputelements for identification of a target data item relative to which thequery is to be processed, selection of a question on a degree ofsimilarity of data items relative to the target data item, selection ofa question on an orientation of data items toward the target data item,and/or entering a time criterion for a query.

In another aspect, the method includes using pictorial or analog valuesymbols to represent one or more of the query parameters on the userinterface. The method further includes visually enhancing one or moredata items in the data plot with one or more of the pictorial or analogvalue symbols used to represent query parameters on the user interface.

In a general aspect, a non-transitory computer readable medium includesinstructions capable of being executed on a processor. The instructionswhen executed allow a computer device to provide a computer-userinterface for formulating and submitting a query relative to a data itemin a data plot, and display the data plot on the computer-user interfacein combination with analog representations of the results of the query.The instructions when executed may cause the computer device to usepictorial or analog value symbols to represent one or more queryparameters on the computer-user interface and use one or more of thesame pictorial or analog value symbols for analog representations of theresults of the analytic query in the display of the data plot.

The details of one or more implementations are set forth in theaccompanying drawings and the description below. Further features of thedisclosed subject matter, its nature and various advantages will be moreapparent from the accompanying drawings the following detaileddescription, and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic block diagram illustrating a hybrid data analysisand visualization tool installed or hosted on a computer system, inaccordance with the principles of the disclosure herein. FIG. 1 alsoillustrates an example user interface of the hybrid data analysis andvisualization tool, which includes a visual data display panel and aquery entry panel, in accordance with the principles of the disclosureherein.

FIG. 2 is an illustration of an example display of a data set in apictorial format and an example schematic representation of query inputelements on the user interface of the hybrid data analysis tool of FIG.1, in accordance with the principles of the disclosure herein.

FIGS. 3-8 are illustrations of example query entry panels of the hybriddata analysis and visualization tool of FIG. 1 that are configured toaccept parameters for pre-defined components of analytic dataexploration queries, in accordance with the principles of the disclosureherein. FIGS. 4, 6, 7, and 8 also illustrate example combined visualdisplays of data plots and query responses generated by the hybrid dataanalysis and visualization tool of FIG. 1, in accordance with theprinciples of the disclosure herein.

FIG. 9 is a flow chart illustration of an example visual dataexploration method combining visual inspection and analytic searchfunctionality, in accordance with principles of the disclosure herein.

DETAILED DESCRIPTION

The term “data exploration” as used herein may refer to techniquesutilized to find one's way through a data set and bring interesting orrelevant aspects or properties of that data into focus. Further, theterms “plot” and “graph” of a data set may be used interchangeablyherein.

An analog representation may be a value or variable in analog orcontinuous form. For example, the position of the hands of a clock is ananalog representation of time. An analog representation may becontrasted with a digital or discrete representation which conveysinformation in terms of discrete, symbolic values. In keeping with thesame example, a digital representation of time is a digital clock, whoserepresentation of time is in terms of discrete variables (e.g.,numbers). Analog representations of information may be more useful inhuman cognition than digital or discrete representations of the sameinformation.

In accordance with the principles of the disclosure herein, a hybriddata analysis and visualization tool combines interactive querycapabilities with a display of a graph or plot of a data set. Theinteractive query capabilities of the data hybrid data analysis andvisualization tool may enable a user to combine visual inspection of theplot of the data set with analytic queries for exploring the data set.The queries may relate to information, properties or characteristics ofthe data that are not explicitly shown or visually discernible in theplot of the data set. In particular, the queries may relate tosimilarities or interrelationships between data items in the data setthat are based on properties or characteristics that depend on variablesother than the plot variables or co-ordinates. The query results may bedisplayed as a part of the plot of the data set. Analog or pictorialrepresentations may be used to display the query results. The analog orpictorial representations may include analog or pictorial values symbols(e.g., arrows, boxes, rings, or other visual indicia). The pictorial oranalog value symbols may include an icon or symbol whose size or shapemay be an analog representation of a query parameter value. Data itemsin the plot may be visually highlighted, annotated, marked or enhancedaccording to the query results to visually convey additional informationabout the data items that is not explicitly shown by the plot itself.The hybrid data analysis tool may allow a user to visually inspect notonly the data items in the plotted data set directly, but to alsovisually inspect the similarities and interrelationships between dataitems in the plotted data set that are uncovered by the queries.

FIG. 1 is a schematic block diagram illustrating a data visualizationtool 10 installed or hosted on a host computer system 100, in accordancewith the principles of the disclosure herein. For economy in words,hybrid data analysis and visualization tool 10 may be referred tohereinafter simply as “data visualization tool 10.”

Data visualization tool 10 may be configured to provide a user withcapabilities to formulate or state queries to visually explore implicitproperties or characteristics of data items in a plot and to visualizehidden relationships between the data items. Data visualization tool 10may provide a user interface (e.g., UI 200) through which a user canformulate and submit queries to visually explore the hiddenrelationships between data items in a plot. A query, in datavisualization tool 10, may be formulated by combining various queryparts or components on the user interface. Each query part or componentmay include graphic visual elements. These graphic visual elements maybe used to highlight data items, which are retrieved or identified onthe basis of user-submitted query, in the plot.

Data visualization tool 10 may be hosted on any suitable computingplatform 12 in computing system 100. Computing system 100 infrastructuremay consist of one or more physical machines, virtual machines, centralprocessing units, disk drives and other resources that may bedistributed over diverse locations or nodes connected by a network. FIG.1 shows, for example, data visualization tool 10 hosted on a computingplatform 12 that is supported, for example, by a processor 13, a memory14 and a display screen 15, and linked to a data source (e.g., database16). Data visualization tool 10 may be hosted on computer system100/computing platform 12 by itself or in conjunction with otherapplications (e.g., business analytics or other data analysis or dataprocessing applications). FIG. 1 shows, for example, data visualizationtool 10 hosted on computing platform 12 in conjunction with a computerapplication 11, which may, for example, be a business analyticsapplication.

FIG. 1 further shows an example user interface (UI) 200 of datavisualization tool 10, in accordance with the principles of thedisclosure herein. In operation, data visualization tool 10 may presentUI 200 to a user, for example, on display screen 15 of computingplatform 12. UI 200 may include a visual data display panel 210 and aquery entry panel 220. Data visualization tool 10 may generate orretrieve data items from a data source (e.g., memory 13, database 16, orother application) to be displayed in a plot in visual data displaypanel 210. The data items generated or retrieved by the computerapplication may be shown in visual data display panel 210 in a pictorialformat (e.g., as a scatterplot, histogram, probability plot, spaghettiplot, residual plot, box plots, block plot or a biplot, etc.) that issuitable for visual inspection by the user.

FIG. 2 shows, for example, a data set D with data items {a, b, c,},which may have been generated or retrieved for display by the hybriddata analysis tool. The data set D may be displayed in visual datadisplay panel 210 of UI 200 in a pictorial format as a scatterplot 215.Scatter plot 215 may use Cartesian coordinates to display data itemvalues in two dimensions (A and B). The data items {a, b, c, . . . } maybe displayed as a collection of points with the position of each pointalong a horizontal co-ordinate axis (e.g., x-Axis) determined by thevalue of one variable in one dimension (A), and its position along avertical co-ordinate axis (e.g., y-Axis) determined by the value of theother variable in the second dimension (B). For example, the position ofdata item a may have a numeric position value a (x1, y1) in scatter plot215, where x1 and y1 are the values of the corresponding variables ofdata item a on the x and y axes, respectively.

In accordance with the principles of the disclosure herein, datavisualization tool 10 may be configured to allow the user to query(e.g., via query entry panel 220) the displayed data set D and/orrelated data sources (e.g., memory 13, database 15, network or otherapplication) for additional information on the displayed data items invisual data display panel 220 of UI 200. Further, data visualizationtool 10 may display the query results in a graphic or pictorial formaton the same plot as the displayed data set D. The graphic or pictorialformat of the displayed query results may include pictorial or analogvalue symbol representations of the query results. Graphical elements,icons, marks or indicia (e.g., highlighting, bold or italicized fonts,boxes, arrows, circles, labels or other symbols or indicia) may be usedto pictorially depict the query results. The graphical or pictorialformat of the displayed query results may visually enhance the displayeddata items of the data set D. The graphical or pictorial format may, forexample, highlight or endow particular data items of the data set D withadditional visual characteristics or features that may make the queryresults amenable to visual inspection by the user and to facilitateexplicit visual exploration of the displayed data set.

A user query on data visualization tool 10 may, for example, relate toimplicit relationships between particular data items in the displayeddata set D. Query entry panel 220 may include one or more input elements(e.g., GUI elements 221-224) that are configured to receive or acceptparameters for defining or stating the user query. GUI elements 221-225may, for example, include one or more of check boxes, menus, analogslider scales, buttons, label buttons, radio buttons, sliders, droplists, text boxes, etc. A user may be able to formulate a query byentering or inputting query parameters in the input elements of queryentry panel 220. The user may use appropriate computer input devices andtechniques (e.g., alpha-numeric character or text entry using akeyboard, point-and-click techniques using a pointer device,hold-and-slide techniques for slider bars, etc.) for entering orinputting the query parameters. Query entry panel 220 may furtherinclude, include an action mechanism (e.g., a “GO” button 226) which theuser can activate to submit a user-formulated query for processing(e.g., by processor 13).

In example implementations of data visualization tool 10, query entrypanel 220 may be configured to accept general or free form queries (i.e.queries of any type) related to the displayed data set. In otherimplementations of data visualization tool 10, query entry panel 220 maybe configured to accept or allow queries with pre-defined components orparts. The one or more input elements (e.g., GUI elements 221-224) maybe accordingly configured to accept input parameters for formulating aquery having the pre-defined components or parts.

A “similarity” type query with respect to a particular data itemdisplayed in visual data display panel 210 may, for example, seek toidentify other data items by the degree of similarity with theparticular data item with regard to an implicit characteristic orproperty of the data items.

EXAMPLE SCENARIO ONE

In an example scenario (“Scenario One”) the data items {a, b, c . . . }displayed in scatter plot 215 may be values of total product sales bydifferent sales entities a, b, c . . . etc. for a given month. For thisscenario, the different sales entities may be represented along thex-axis and their total monthly product sales may be represented alongthe y-axis to define the positions of displayed data items {a, b, c . .. } in scatter plot 215. The displayed total monthly product sales {a,b, c . . . } may have implicit characteristics or properties (e.g., amix of different types of products sold, a rate of change in monthlysales amounts, profitability, etc.) that are not explicitly shown in, orevident upon visual inspection of scatter plot 215. An examplesimilarity query with reference to a data item m may, for example, seekto identify other data items that have a similar characteristic orproperty (e.g., a similar product mix, a similar rate of change in theamount of monthly product sales, etc.) as sales entity m.

FIG. 3 shows an example query entry panel 320 of data visualization tool10/UI 200 that is configured to accept parameters for pre-definedcomponents of queries in scenarios such as Scenario One. A firstpre-defined query component in query entry panel 320 may, for example,pose a query question on which other data items have a similar path as atarget data item. A second pre-defined query component in query entrypanel 320 may pose a query question on which data items have anorientation toward the target data item.

Query entry panel 320 may have a customized arrangement of input areasor GUI elements that are configured to receive or accept parameters forthe pre-defined query component questions. The customized input elementsof query entry panel 320 may, for example, include a text box 312, whichis labeled as “Target”, for identifying a target data item relative towhich the pre-defined query questions may be processed. The target dataitem may be but need not be a data item that is already displayed inscatter plot 215. Data visualization tool 100 may allow a user to selecta target data element (e.g., data item m) for the queries, for example,by entering text (e.g., “m”) in text box 312 and/or by marking orselecting the target data element (e.g., by pointing and clicking on thetarget data element m) if it is already displayed in scatter plot 215.

Further, the input elements in query entry panel 320 may include radiobuttons or check boxes (e.g., check boxes 314 and 318), which allow auser to select one or more of the two pre-defined query questions toinclude in a query. For the first pre-defined query question on whichother displayed data items have a similar path as the target data item,query entry panel 320 may include an input box 315 which allows a userto select a degree of similarity threshold or metric (e.g., low to highsimilarity) for the query. Input box 315 may include, for example, aslider 316 that allows the user to select the value of the similaritymetric (e.g., between a low and a high value) on an analog sliding scale319. Suitable graphical icons (e.g., rings 317 of differentthicknesses), which pictorially represent varying values of similarityfrom low to high along the analog sliding scale, may be used as visualaids to guide the user's selection of the value of the degree ofsimilarity metric for the query question. Input box 315 may be displayedcontinuously in query entry panel 320 or only as a pop-up window thatappears only when the user selects a check box (e.g., check box 314).

After a user has formulated the query question (e.g., by identifying atarget data item in text box 312, marking check box 314 for thesimilarity question, and positioning slider 316 to select a value forthe degree of similarity metric), the user may submit the query questionfor processing by activating an action button (e.g., GO button 326) onquery entry panel 320.

Query processing by data visualization tool 10 may result inidentification of qualified data items which fulfill at least the degreeof similarity to the target data item that was indicated by the positionof slider 316 in the user-submitted query. The qualified data items mayinclude data items that were already present in scatter plot 215 (e.g.,data items o, q, b, etc.) and/or may include data items that were notalready present in scatter plot 215 but are available in the querieddata source (e.g., memory 13, or database 16).

The query response or results may be displayed by data visualizationtool 10 in visual data display panel 210 for visual inspection by theuser. FIG. 4 shows example query results displayed on visual datadisplay panel 210 in response to the user-submitted similarity query inScenario One. In the example query results shown, the target data item(e.g., data item m) and qualified data items (e.g., data items o, q andb), which fulfill at least the degree of similarity metric that wasindicated by the position of slider 316 in the user-submitted query, maybe highlighted to facilitate visual identification or inspection by theuser. The target data item m may be highlighted using the same icon(e.g., text box icon 312) used to identify it in query entry panel 320.Further, the qualified data items (e.g., data items o, q and b) may behighlighted using the same graphical icons (e.g., rings of differentthicknesses 317) that pictorially represent varying degrees ofsimilarity in the legend for the analog sliding scale 319 in query entrypanel 320. These highlighting graphical icons may visually inform theuser of the degree of similarity of each of the qualified data items tothe target data item. Further, the query response displayed on visualdata display panel 210 may additionally include visual indicators ormarkers (e.g., arrows 417) that show relative paths or trends of thequalified data items and the target data item.

It will be noted that the query response displayed in FIG. 4 includeshighlighting of the similarity characteristics of the query-retrievedqualified data items and the target data item. However, some versions ofdata visualization tool 10 may further include a switch control or UIfeature that enables a user to view the similarity or othercharacteristic of any particular data item displayed in visual datadisplay panel 210 even if that particular data item is not aquery-retrieved qualified data item.

In a version of data visualization tool 10, the query processing mayretrieve qualified data items from a source database (e.g., memory 13,database 16, etc.) that were previously not displayed in scatter plot215 if they fulfill the query criteria for similarity to the target dataitem (e.g., data item m). Similarly, the same or other version of datavisualization tool 10 may allow a user to run queries relative to atarget data item that was not previously displayed in scatter plot 215(e.g., by explicitly entering target data item identifying-text in inputbox 315). These previously un-displayed data items and their similaritycharacteristics may be displayed and highlighted in the query responsepresented by data visualization tool 10 on visual data display panel 210in the same manner as the previously-displayed qualified data items(e.g., data items o, q and b) are displayed and highlighted as describedabove with reference to FIG. 4.

EXAMPLE SCENARIO TWO

In another example scenario (“Scenario Two”) the data items {a, b, c . .. } shown in scatter plot 215 may, for example, represent a currentmeasure of business competitiveness of entities a, b, c, etc. The dataplotted in scatterplot 215 may explicitly convey visual information onthe current competitiveness values of the entities a, b, c, etc. to auser. However, the displayed data items {a, b, c . . . } may haveimplicit characteristics or properties (e.g., short term and long termtrends, or rate of change in competitiveness), which are not explicitlyshown in or evident upon visual inspection of scatter plot 215 of thedata items {a, b, c . . . }. For data exploration in such a scenario,another example query entry panel of data visualization tool 10/UI 200may include pre-defined queries that focus on the degree ofcorrespondence between paths of a target data item and other data items.

FIG. 5 shows an example query entry panel 520 with pre-defined queriesthat that focus on the degree of correspondence between a path of atarget data item and other data items in scenarios such as Scenario Two.Like the input elements of query entry panel 320 shown in FIG. 3, theinput elements of query entry panel 520 may include radio buttons orcheck boxes (e.g. check boxes 314 and 318), which allow a user to selecteither of the pre-defined similarity or orientation query questions tosubmit for processing. For the query question on which of the otherdisplayed data items have an orientation toward the target data item,query entry panel 520 may include an input box 515 which allows a userto select a level of orientation metric (e.g., a low to a high level oforientation) for the query. Input box 515 may include a slider 516,which allows the user to select the level of orientation metric on ananalog sliding scale. Suitable graphical icons (e.g., rings of differentthicknesses 517), which pictorially represent varying levels oforientation from low to high along the analog sliding scale, may be usedas a visual aid to guide user selection of the level of orientationmetric for formulating the query question. Like input box 315 on queryentry panel 320, input box 515 may be displayed on query entry panel 520continuously or as a pop-up window that appears only when the userselects a query check box (e.g., check box 318).

After a user has formulated the query question (e.g., by entering targetdata item identifying-text m in text box 312, marking check box 318 forthe orientation question, and positioning slider 516 to select a levelof orientation metric), the user may submit the query question forprocessing by activating an action button (e.g., GO button 526) on queryentry panel 520.

Processing by data visualization tool 10 of the user-submitted query mayresult in identification of qualified data items which fulfill at leastthe level of orientation toward the target data item that was indicatedby the position of slider 516 in the user query. The qualified dataitems may include data items that were already present in scatter plot215 (e.g., data items i, n, o, q and b). The query results may bedisplayed pictorially by data visualization tool 10 in visual datadisplay panel 210 for visual inspection by the user.

FIG. 6 shows example query results displayed on visual data displaypanel 210 in response to the user-submitted similarity query in ScenarioTwo. In the display, the qualified data items (e.g., data items i, n, o,q and b) may be highlighted to facilitate visual identification orinspection, using, for example, the same graphical icons (e.g., rings ofdifferent thicknesses 517) that pictorially represent varying levels oforientation in the legend for the analog sliding scale in input box 515.

The query response displayed on visual data display panel 210 mayinclude additionally visual indicators or markers (e.g., arrows 518)that pictorially illustrate the relative orientation and strength withwhich the qualified data items are moving toward the target data item m.For example, as shown in FIG. 6, the direction and the thickness ofarrow 518 associated with qualified data item a may visually suggest tothe user that entity a has business competitiveness measure that isstrongly increasing up ward to that of the target data item m. Thedirection and the thickness of arrow 518 associated with qualified dataitem n may, for example, visually suggest to the user that entity n hasbusiness competitiveness measure that is increasing less strongly thanqualified data item a toward a value below that of the target data itemm. Similarly, the direction and the thickness of arrows 518 associatedwith data items o and q may visually suggest to the user that entities oand q have business competitiveness measures that are either decreasingor are directed away from that of the target data item m.

It will be noted that the query response displayed in FIG. 6 includeshighlighting of the orientation characteristics of the query-retrievedqualified data items and the target data item, However, some versions ofdata visualization tool 10 may further include a switch control or UIfeature that enables a user to view the orientation characteristics orother characteristic of any particular data item displayed in visualdata display panel 210 even if that particular data item is not aquery-retrieved qualified data item.

It will be understood that the types of queries or the query parametersthat may be used with data visualization tool 10/UI 200 are not limitedto the examples described above with reference to FIGS. 3-6. FIGS. 7 and8 show example versions of data visualization tool 10/UI 200 in whichthe composition of the pre-defined queries described above withreference to FIGS. 3-6 are modified or extended to include display oftemporal criteria.

FIG. 7 shows an example query entry panel 720 in which the queryquestion on which of other data items have a similar path as a targetdata item (shown on query entry panel 320) is extended with querycomponents that are based on time criteria. In particular, query entrypanel 720 may include an input box 715 with sliding time markers 716 ona sliding scale that allow the user to enter time criteria in additionto a degree of similarity criteria (input box 315) for formulating thequery question on which of other data items have a similar path as atarget data item. Like input box 315, input box 715 may be displayed onquery entry panel 720 continuously or as a pop-up window that appearsonly when the user selects a query check box (e.g., check box 314).

A user may select a time interval criterion for the query, for example,by suitably positioning or setting sliding time markers 716 at differentbeginning and ending times (e.g., Q3 2011 and Q1 2012) on the slidingscale in input box 715. The selected time interval may be representedpictorially in query entry panel 720 by a graphical icon (e.g., arrow717) extending between the positions of sliding time markers 716 set bythe user. In this example, query processing by data visualization tool10 may result in identification of qualified data items which meet thedegree of similarity criteria (indicated by the position of slider 316)over time interval 717 that was indicated by the positions of slidingtime markers 716. In the same manner that the similarity characteristicsof the qualified data items returned by the query are highlighted usingthe graphical icons (e.g., rings of different thicknesses 317) used inquery entry panel 320 in FIG. 4, the similarity and time characteristicsof the displayed query results here may be highlighted using the samegraphical icons that are used to represent the similarity and timecharacteristics in the query entry panel 720. FIG. 6 shows, for example,qualified data items o, n and b that are visually highlighted using thesame rings of varying thickness 317 and arrows 717 that are used asgraphical icons for the respective query characteristics in query entrypanel 720.

FIG. 8 shows an example query entry panel 820 in which the queryquestion on which other displayed data items have an orientation towardthe target data item (query entry panel 520) is extended with furtherquery components based on time parameters. In particular, query entrypanel 820 may include a first input box 815 and a second input box 825for adding time criteria to the orientation query that may be set inquery entry panel 520. For visual clarity, only first input box 815 andsecond input box 825 are shown and other query components (e.g., inputbox 515) are omitted from FIG. 8.

Like input box 715 of query entry panel 720, first input box 815 andsecond input box 825 may include pairs of sliding time markers (e.g.,time markers 816 and 826) on sliding scales that allow the user to entertime criteria for formulating the query question on which of other dataitems have orientations toward the target data item. Further like inputbox 715, first input box 815 and second input box 825 may be displayedon query entry panel 820 continuously or as pop-up windows that appearonly after the user selects a query check box (e.g., check box 318).

In the same manner as described above for selecting a time intervalcriterion using input box 715 in query entry panel 720, a user mayselect time interval criteria (e.g., a short time interval and a longtime interval) for the query, for example, by suitably positioning orsetting sliding time markers 816 and 826 on the sliding scales in firstinput box 815 and second input box 825, respectively. The user-selectedshort and long time intervals may, for example, be about one about oneyear long (e.g., extending from 4Q 2011 to 4Q 2012) and one quarter yearlong (e.g., extending from 3Q 2012 to 4Q 2012), respectively, as shownin FIG. 8. The selected long time and short time intervals may berepresented pictorially in query entry panel 820 by graphical icons(e.g., arrows 817 and 827, respectively).

In this example, query processing by data visualization tool 10 mayresult in identification of qualified data items which meet at least thelevel of orientation toward the target data item that was indicated bythe position of slider 516 (shown in query entry panel 520) in the usersubmitted-query over both the long time interval 817 and the short timeinterval 827. As in the previous examples described herein, datavisualization tool 10 may highlight query results presented in thevisual data display panel 210 using the same graphical icons used thatare used to visually illustrate query components in the query entrypanel 820. FIG. 8 shows, for example, qualified data items i and ndisplayed in scatter plot 215 that are highlighted or enhanced by bothlong time interval arrows 817 and short interval arrows 827 that areused to visually illustrate query time interval components in queryentry panel 820. For visual clarity, highlighting of other querycriteria (e.g., level of orientation criteria) other than the temporalcriteria is omitted in FIG. 8.

Adding query components and highlighting them in the display of queryresults as in the forgoing examples may enable a user to visuallyexplore data in detail. For example, the display of query results inFIG. 8 may allow a user to discern that the orientations of both dataitems i and n were moving vertically upward over the one year timeinterval as visually highlighted by the long time interval arrows 817.However, as visually highlighted by short interval arrows 818, thedisplayed data shows both data items i and n changed course over thelast one quarter year time interval. A user can visually discern fromthe query result display in FIG. 8 in detail that data item i is nowmoving away from target data item m and data item n is moving towardtarget data item m as indicated by the directions of thedata-highlighting short interval arrows 818.

FIG. 9 shows an example computer-implemented method 900 for exploringdata that is displayed in a data plot on a user interface, in accordancewith the principles of the disclosure herein. Method 900 includesproviding a computer-user interface that is configured to allow a userto formulate and submit a query on the data that is displayed in thedata plot (910), processing the user-submitted query (920), anddisplaying the data plot on the computer-user interface in combinationwith analog representations of results of the query (930). Theuser-submitted query may relate to implicit properties of data items inthe data plot that may not be evident up on visual inspection of thedata plot itself.

Providing a computer-user interface configured for a user to formulateand submit a query on the data that is displayed in the data plot 910may include providing input elements for entering query parameters forone or more pre-defined query components on the computer-user interface(912). The pre-defined query components of the query on the userinterface may, for example, include identification of a target data itemrelative to which the query is to be processed, a question on a degreeof similarity of data items relative to the target data item, a queryquestion on which data items have an orientation toward the target dataitem, and/or components defining bounds (e.g., upper limits, lowerlimits or ranges) for query parameters (e.g., time), etc. The inputelements may include one or more of check boxes, menus, analog sliderscales, buttons, label buttons, radio buttons, sliders, drop lists, textboxes, etc.

Providing input elements for entering query parameters for one or morepre-defined query components on the computer-user interface 912 mayinclude providing one or more input elements for identification of atarget data item relative to which the query is to be processed, a queryquestion on a degree of similarity of data items relative to the targetdata item, a query question on an orientation of data items toward thetarget data item, and/or entering a time criterion for a query.Providing input elements for entering query parameters for one or morepre-defined query components on the computer-user interface 912 may alsoinclude using pictorial or analog value symbols to represent one or moreof the query parameters for the one or more pre-defined query componentson the user interface (914). The pictorial or analog value symbols mayinclude, for example, arrows, boxes, rings, or other visual indicia. Thepictorial or analog value symbols may include an icon or symbol whosesize or shape may be an analog representation of a query parametervalue. Further, displaying the data plot on the computer-user interfacein combination with analog representations of results of the query 930may include visually enhancing one or more data items in the data plotwith one or more of the pictorial or analog value symbols that are usedto represent query parameters the one or more pre-defined querycomponents on the user interface (932).

The various systems and techniques described herein may be implementedin digital electronic circuitry, or in computer hardware, firmware,software, or in combinations of them. The various techniques mayimplemented as a computer program product, i.e., a computer programtangibly embodied in an information carrier, e.g., in a machine readablestorage device or in a propagated signal, for execution by, or tocontrol the operation of, data processing apparatus, e.g., aprogrammable processor, a computer, or multiple computers. A computerprogram, such as the computer program(s) described above, can be writtenin any form of programming language, including compiled or interpretedlanguages, and can be deployed in any form, including as a standaloneprogram or as a module, component, subroutine, or other unit suitablefor use in a computing environment. A computer program can be deployedto be executed on one computer or on multiple computers at one site ordistributed across multiple sites and interconnected by a communicationnetwork.

Method steps may be performed by one or more programmable processorsexecuting a computer program to perform functions by operating on inputdata and generating output. Method steps also may be performed by, andan apparatus may be implemented as, special purpose logic circuitry,e.g., an FPGA (field programmable gate array) or an ASIC (applicationspecific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read only memory ora random access memory or both. Elements of a computer may include atleast one processor for executing instructions and one or more memorydevices for storing instructions and data. Generally, a computer alsomay include, or be operatively coupled to receive data from or transferdata to, or both, one or more mass storage devices for storing data,e.g., magnetic, magnetooptical disks, or optical disks. Informationcarriers suitable for embodying computer program instructions and datainclude all forms of nonvolatile memory, including by way of examplesemiconductor memory devices, e.g., EPROM, EEPROM, and flash memorydevices; magnetic disks, e.g., internal hard disks or removable disks;magnetooptical disks; and CDROM and DVD-ROM disks. The processor and thememory may be supplemented by, or incorporated in special purpose logiccircuitry.

To provide for interaction with a user, implementations may beimplemented on a computer having a display device, e.g., a cathode raytube (CRT) or liquid crystal display (LCD) monitor, for displayinginformation to the user and a keyboard and a pointing device, e.g., amouse or a trackball, by which the user can provide input to thecomputer. Other kinds of devices can be used to provide for interactionwith a user as well; for example, feedback provided to the user can beany form of sensory feedback, e.g., visual feedback, auditory feedback,or tactile feedback; and input from the user can be received in anyform, including acoustic, speech, or tactile input.

Implementations may be implemented in a computing system that includes abackend component, e.g., as a data server, or that includes a middlewarecomponent, e.g., an application server, or that includes a frontendcomponent, e.g., a client computer having a graphical user interface ora Web browser through which a user can interact with an implementation,or any combination of such backend, middleware, or frontend components.Components may be interconnected by any form or medium of digital datacommunication, e.g., a communication network. Examples of communicationnetworks include a local area network (LAN) and a wide area network(WAN), e.g., the Internet.

While certain features of the described implementations have beenillustrated as described herein, many modifications, substitutions,changes and equivalents will now occur to those skilled in the art. Itis, therefore, to be understood that the appended claims are intended tocover all such modifications and changes as fall within the scope of theembodiments.

What is claimed is:
 1. A computer device, comprising: a processor; and adata visualization tool configured to display data items of a data setin a graph and display a query panel associated with the graph, thequery panel including one or more data entry fields to receive queriesregarding properties of one or more specific data items in the graphrelative to a target data item, the data visualization tool furtherconfigured to, in response to a user-entered query on the query panelregarding a visually unrepresented property of the specific data itemsdisplayed in the graph relative to the target data item, assign adiscrete value selected from a continuous range of analog values torepresent the visually unrepresented property returned by the query, andadd an analog representation of the discrete value selected from thecontinuous range of analog values to represent the visuallyunrepresented property returned by the data query into the displayedgraph of the data items, wherein the query panel includes at least oneinput element for selecting one or more pre-defined queries, the one ormore pre-defined queries including a pre-defined query having a degreeof similarity between the data items relative to the target data item asa query parameter, and wherein data items which have a queried degree ofsimilarity to the target item with respect to an implicit property ofthe data items are identified on the displayed graph upon submission ofthe pre-defined query for processing.
 2. The computer device of claim 1,wherein the data visualization tool includes interactive features forsubmitting data queries and for viewing analog representations of thedata query results visually in combination with the graph of the dataitems on a user interface.
 3. The computer device of claim 2, whereinthe data visualization tool includes interactive features for submittinga data query relative to a target data item displayed in the graph ofthe data items on the user interface.
 4. The computer device of claim 2,wherein the user interface includes a visual data display panel and aquery entry panel.
 5. The computer device of claim 4, wherein the queryentry panel includes one or more input elements for entering queryparameters.
 6. The computer device of claim 1, wherein the pre-definedquery components include a question on an orientation of data itemstoward the target data item.
 7. The computer device of claim 1, whereinthe pre-defined query components include a time criterion.
 8. Thecomputer device of claim 1, wherein the one or more input elements forentering query parameters for pre-defined query components include oneor more of check boxes, menus, analog slider scales, buttons, labelbuttons, radio buttons, sliders, drop lists, and text boxes displayed onthe query entry panel.
 9. The computer device of claim 1, wherein theone or more input elements for entering query parameters on the queryentry panel are displayed with pictorial representations of the queryparameters.
 10. The computer device of claim 9, wherein the datavisualization tool is configured use the pictorial representations ofthe query parameters on the query entry panel in conjunction with theanalog representations of data query results to enhance the graph of thedata set.
 11. A computer-implemented method for exploring data that isdisplayed in a data plot, the method comprising: providing acomputer-user interface configured to allow a user to formulate andsubmit a query regarding on a visually unrepresented property of aspecific item of the data that is displayed in the data plot relative toa target data item: assigning a discrete value selected from acontinuous range of analog values to represent the visuallyunrepresented property returned by the query; and displaying an analogrepresentation of the discrete value selected from the continuous rangeof analog values to the visually unrepresented property of the specificitem of the data relative to the target data item returned by the queryin the data plot in addition to the data that is displayed in the dataplot, wherein providing a computer-user interface configured for a userto formulate and submit a query on the data that is displayed in thedata plot includes providing an input element for entering a queryparameter of a pre-defined query on the user interface, whereinproviding an input element for entering a query parameter includesproviding an input element for a selecting a degree of similarity ofdata items relative to the target data item with respect to an implicitproperty of the data items as the query parameter of the pre-definedquery, and wherein data items which have a selected degree of similarityrelative to the target item with respect to the implicit property of thedata items are identified on the data plot upon submission of thepre-defined query for processing.
 12. The method of claim 11, whereinproviding input elements for entering query parameters further includeproviding an input element for at least one of: identification of a thetarget data item relative to which the query is to be processed; andselection of a question on an orientation of data items toward thetarget data item.
 13. The method of claim 11, wherein providing inputelements for entering query parameters include providing an inputelement for entering a time criterion for a query.
 14. The method ofclaim 11, wherein providing input elements for entering query parametersincludes using one or more of pictorial and analog value symbols torepresent one or more of the query parameters on the user interface. 15.The method of claim 14, wherein displaying analog representations of theimplicit properties of the data revealed by the query in the data plotin addition to the data that is displayed in the data plot includesvisually enhancing one or more data items in the data plot with one ormore of the pictorial symbols used to represent query parameters on theuser interface.
 16. A non-transitory computer readable medium,comprising: instructions capable of being executed on a processor, whichinstructions when executed allow a computer device to: display dataitems of a data set in a data plot; provide a computer-user interfacefor formulating and submitting a query regarding a visuallyunrepresented property of a specific data item in the data plot relativeto a target data item: assign a discrete value selected from acontinuous range of analog values to represent the visuallyunrepresented property returned by the query; and display an analogrepresentation of the discrete value selected from the continuous rangeof analog values to represent the visually unrepresented propertyreturned by the query in the data plot in addition to the displayed dataitems in the data plot; wherein providing a computer-user interfaceconfigured for a user to formulate and submit a query includes providingan input element for entering a query parameter of a pre-defined queryon the user interface, wherein providing an input element for entering aquery parameter includes providing an input element for a selecting adegree of similarity of data items relative to the target data item withrespect to an implicit property of the data items as the query parameterof the pre-defined query, and wherein data items which have a selecteddegree of similarity relative to the target item with respect to theimplicit property of the data items are identified on the data plot uponsubmission of the pre-defined query for processing.
 17. Thenon-transitory computer readable medium of claim 16, wherein theinstructions when executed on the processor cause the computer device touse one or more of pictorial and analog value symbols to represent oneor more query parameters on the computer-user interface.
 18. Thenon-transitory computer readable medium of claim 17, wherein theinstructions when executed on the processor cause the computer device touse one or more of the one or more of pictorial and analog value symbolsthat represent one or more query parameters on the computer-userinterface for analog representations of the results of the query in thedisplay of the data plot.